In digital cameras with video recording capability, one of the desired features is the ability to zoom and focus while video recording. Most cameras with this built-in feature suffer from the problem of the user hearing the sound of the zoom motor picked up by on-camera microphones.
FIG. 1 is a simple block diagram of the camera where Mic1 and Mic2 are the two microphones used on the camera for audio stereo recording, S1 represents the desired voice or audio signal that should be recorded by the camera with minimum distortion and S2 represents the audio noise generated by the zoom or lens focus motor. Also in this figure, h21 and h22 represent the acoustic paths between the motor and the two microphones. Due to the small size of video cameras, the motor will be in close proximity of the two microphones and as a result most of the noise generated by zoom or focus motors will be picked up by the two microphones. To most users this noise is annoying and desirably should be eliminated.
A rather expensive way of achieving this result is to use quieter zoom and focus motors. This may not be a cost effective solution, especially for low cost cameras. Another approach to this problem is to remove the noise by performing digital signal processing on the microphone signals.
In most cameras the audio signals from the microphones signals are digitized using analog to digital (A/D) converters and processed by an embedded processor, which may also compress the recorded audio signals before saving them into a flash memory.
A signal processing algorithm for removing the motor noise from input audio signal can be made part of the software running on the camera processor, ideally before audio compression stage. This solution can be very cost effective since it only requires a software upgrade rather than modification to expensive hardware.
Although very cost effective, removing camera motor noise through digital processing of the microphone signals is a non-trivial task. The main challenge is that removing the motor noise should not distort input audio signal. Camera zoom motor noise is wideband and quasi stationary in nature, and it shares same frequency bands with the input audio signal itself. As a result, such noise cannot be eliminated using traditional DSP filtering techniques (e.g. lowpass filtering, notch filter etc.). Also single microphone noise reduction methods which rely on subtracting noise spectrum from the input signal spectrum are not very attractive since they tend to distort the original audio signal. To make matters worse, the spectrum of motor noise may change with time. This can affect the performance of the algorithms that mainly rely on a stationary noise assumption.
Other approaches such as beamfoming and active noise control (ANC) have their own limitations. For example, for beamforming the geometry and number of microphones and their location affects the output performance. Also beamforming or similar approaches may require a greater number of microphones (more than two) which may not feasible on a small camera body. In addition, these methods are usually computationaly expensive to implement.